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Research Article DOI:10.13179/canchemtrans.2014.02.01.0059
Research on the Batch and Fixed-Bed Column Performance
of Red Mud Adsorbents for Lead Removal
Iman Mobasherpour
*, Esmail Salahi and Ali Asjodi
Ceramics Department, Materials and Energy Research Center, P.O. Box 31787-316, Karaj, Iran
*Corresponding Author, E-mail: [email protected], [email protected]
Tel: +98(261)6204131
Received: November 5, 2013 Revised: December 23, 2013 Accepted: December 23, 2013 Published: December 24, 2013
Abstract: The removal of lead from water by red mud using batch and fixed-bed column adsorption
techniques was investigated. In a batch study, experiments indicated that the time to attain equilibrium
was 2h. The experimental data fitted well to a Langmuir adsorption isotherm and the adsorption capacity
was 18.87 mg/g. Fixed-bed column experiments were carried out for different influent lead
concentrations, bed depths, and various flow rates. The breakthrough time and exhaustion time decreased
with increasing flow rate, decreasing bed depth and increasing influent lead concentration. The bed depth
service time model and the Thomas model were applied to the experimental results. Both model
predictions were in good agreement with the experimental data for all the process parameters studied,
indicating that the models were suitable for red mud fix-bed column design.
Keywords: Red Mud; Pb2+
Contamination; Adsorption; Removal of Heavy Metal
1. INTRODUCTION
Water pollution is the contamination of water bodies such as lakes, rivers, oceans, and
groundwater caused by human activities, which can be harmful to organisms and plants which live in
these water bodies. Water pollution by toxic heavy metals through the discharge of industrial waste is a
worldwide environmental problem. The presence of heavy metals in streams, lakes, and groundwater
reservoirs has been responsible for several health problems with plants, animals, and human beings [1].
Heavy metal contamination exists in aqueous waste stream from many industries such as metal plating,
mining, tanneries, painting, car radiator manufacturing, as well as agricultural sources where fertilizers
and fungicidal spray are intensively used [2,3].
Lead is one of the most ubiquitous contaminants in the soil and aqueous environments. A severe
environmental Pb contamination can often be found at shooting ranges where the soil Pb concentration
sometimes exceeds 10000 mg kg-1
because of spent lead bullets. In Iran, many shooting ranges are
generally located in mountainous regions and suffer from the degradation of natural vegetation due to Pb
toxicity, which may have the potential to augment the Pb contamination via soil erosion. Therefore,
development of cost-effective technologies is necessary to reduce the mobility and bioavailability of Pb in
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soil and water environments [4,5].
Studies proved that metals such as lead, copper, zinc, nickel, chromium, and mercury which have
been considered as hazardous heavy metals are very toxic elements and they are commonly found in
water and wastewater. So, the removal of these metals from wastewater is necessary. In wastewater
treatment technology, various methods have been used to remove heavy metals from aqueous solutions.
Traditional methods for the removal and recovery of heavy metals from industrial waste streams are
precipitation, ion exchange, electrolysis, adsorption on activated carbon, etc. Most of these methods are
extremely expensive or inefficient, especially for a large amount of solution at relatively low
concentrations [6–9]. Among the various water-treatment techniques described, adsorption is generally
preferred for the removal of heavy metal ions due to its high efficiency, easy handling, availability of
different adsorbents and cost effectiveness. Recently, there has been an increasing emphasis on the
adsorbent with low cost for the heavy metal ions removal. Most cases have also confirmed that the use of
large quantities of such kind of wastes for the treatment of polluted water is an attractive and promising
option with a double benefit for the environment [10–12].
Red mud emerges as a residue during alkaline-leaching of bauxite in Bayer process. Roughly 1–2
tons of red mud residues are produced for a ton of alumina [13]. Since the plant began to process, red mud
has accumulated over years and causes a serious environmental problem due to its high alkalinity and
large amount. Many have studied the application of red mud in wastewater treatment and red mud has
been found to remove chromium [14], hexavalent [15], dyes [16], and heavy metals [17], from aqueous
solution. Due to the high percentages of calcium, aluminum and iron, red mud is a good candidate for use
as an economic adsorbent for large-scale use.
The present study sought to investigate Jajarm red mud as an alternative lead adsorbent. The
objectives were to: (i) perform batch studies to examine lead adsorption using red mud (effect of initial
lead concentration and adsorption isotherm) and (ii) perform column studies to investigate the lead uptake
characteristics of red mud under different flow rates.
2. EXPERIMENTAL
2.1. Preparation of adsorbent
Red mud has been obtained as bauxite waste in the manufacture of alumina and emerges as
unwanted by-products during alkaline-leaching of bauxite in Bayer process. The alkaline red mud-water
pump has been dumped annually into specially constructed dams around the Jajarm Aluminum Plant
(Jajarm, Iran). Red mud used in this experimental study has been obtained from this plant.
The alkaline red mud was thoroughly washed with distilled water until it became neutral. The
suspension was wet sieved through a 200mesh screen. A little amount of the suspension remained on the
sieve and was discarded. The solid fraction was washed five times with distilled water following the
sequence of mixing, settling, and decanting. The last suspension was filtered, and the residual solid was
then dried at 105 º C, ground in a mortar, and sieved through a 200 mesh sieve. The product was used in
the study.
The average chemical composition of red mud was listed in Table 1. This table showed that red
mud is primarily a mixture of Ca, Si, Fe and Al oxides and the CaO content is the highest. The single-
point N2-BET method indicated that the specific surface area of a typical red mud sample was about
8.12m2/gr. The red mud agglomerates by many small compact particles as shown by SEM in Fig. 1.
According to the XRD pattern shown in Fig. 2, the identified mineral phases in the red mud are mainly
gibbsite [Al(OH)3], cristobalite [SiO2], hematite [Fe2O3], calcium carbonate [CaCO3], sodium oxide
[Na2O], periclase [MgO] and anatase [TiO2].
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Table 1. Chemical analysis characterization of Red mud
Chemical analysis of red mud
Composition (wt%) CaO Al2O3 SiO2 Fe2O3 Na2O MgO TiO2
24.0 19.0 18.8 15.7 7.8 6.6 6.4
Figure 1. SEM images of red mud
Figure 2. XRD pattern of red mud
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2.2. Batch adsorption experiments
Aqueous solutions containing Pb2+
ions of concentration 30, 40, 50 and 100 mg/L were prepared
from Lead nitrate (Pb(NO3)2, Merck No.7397). 1 g of red mud was introduced in a stirred tank reactor
containing 500 ml of the prepared solution. The stirring speed of the agitator was 300 rpm. The
temperature of the suspension was maintained at 20 ±1 ° C. The initial pH of the solution was adjusted to
the value 7.5 by adding NH3 and HCl. Samples were taken after mixing the adsorbent and Pb2+
ion
bearing solution at pre determined time intervals (5, 10, 20, 30, 60, and 120 min) for the measurement of
residual metal ion concentration in the solution and to ensure equilibrium was reached. After specified
time the sorbents were separated from the solution by centrifuge and filtration through the filter paper
(Whatman grade6). The exact concentration of metal ions was determined by AAS (GBC 932 Plus atomic
absorption spectrophotometer). All experiments were carried out twice. The mass balance of lead is given
by:
mq =V (C0-C) (1)
Where m is the weight of red mud (g), q the amount of lead removed by unit of weight of red mud
(Uptake capacity: mg Pb/g red mud), V the volume of lead solution (L), C0 the initial lead concentration
of solution (mg Pb/L) and C is the concentration of lead at the time t of adsorption (mg Pb/L). After a
long time (120 min), C and q will reach equilibrium value Ce and qe.
2.3. Column adsorption experiments
Continuous flow adsorption experiments were conducted in glass columns of 1.0 cm inside
diameter. At the top of the column, the influent lead solution (30, 40 and 50 mg Pb/L) was pumped
through the packed column (5, 7 and 10 cm), at flow rates of 3, 5 and 7 mL/min, using a peristaltic pump.
Samples were collected from the exit of the column at regular time intervals and analyzed for residual
lead concentration (GBC 932 Plus atomic absorption spectrophotometer).
3. RESULTS AND DISCUSSION
3.1. Batch adsorption experiments
3.1.1. Effect of contact time and initial Pb2+
concentration
As shown in Fig. 3, the lead adsorption process took place in two stages. The first rapid stage in
which 80–90% adsorption was achieved in 10 min, and a slower second stage, with equilibrium attained
in 2 h. The first stage was due to the initial accumulation of lead at the red mud surface, as the relatively
large surface area was utilized. With the increasing occupation of surface binding sites, the adsorption
process slowed. The second stage was due to the penetration of lead ions to the inner active sites of the
adsorbent. This concurs with the observations in similar studies [18, 19].
The sorption of Pb2+
cations was carried out at different initial lead concentrations ranging from
30 to 100 mg/L, at pH 7.5, at 300 rpm with 120 min of contact time using red mud. The uptake of the Pb2+
ion is increased by increasing the initial metal concentration tending to saturation at higher metal
concentrations. As shown in Fig. 4.When the initial Pb2+
cations concentration increased from 30 to 100
mg/L, the uptake capacity of red mud increased from 12 to 18 mg/g. A higher initial concentration
provided an important driving force to overcome all mass transfer resistances of the pollutant between the
aqueous and solid phases thus increased the uptake [20].
3.1.2. Adsorption isotherms
Analysis of the equilibrium data is important to develop an equation which accurately represents
the results and which could be used for design purposes [21]. Several isotherm equations have been used
for the equilibrium modeling of adsorption systems. The sorption data have been subjected to different
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sorption isotherms, namely, Langmuir, and Freundlich. The equilibrium data for lead cations over the
concentration range from 30 to 100 mg/L at 20C have been correlated with the Langmuir isotherm [22]:
Figure 3. Effect of initial concentration of lead on adsorption as a function of contact time
Figure 4. Effect of initial concentration on removal of Pb2+
by red mud sorbents (pH 7.5, adsorbent
dosage = 2gr/L, 300rpm agitating rate)
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QC
KQqC e
e
e
00
1 (2)
Where Ce is the equilibrium concentration of lead in solution (mg/L), qe is the amount absorbed at
equilibrium onto red mud (mg/g), Q0 and K are Langmuir constants related to sorption capacity and
sorption energy, respectively. Maximum sorption capacity (Q0) represents monolayer coverage of sorbent
with sorbate and K represents enthalpy of sorption and should vary with temperature. A linear plot is
obtained when Ce/qe is plotted against Ce over the entire concentration range of metal ions investigated.
The linearized Langmuir adsorption isotherms of Pb2+
ions are given in Fig.5. (a). An adsorption isotherm
characterized by certain constants which values express the surface properties and affinity of the sorbent
and can also be used to find the sorption capacity of sorbent.
The Freundlich sorption isotherm, one of the most widely used mathematical descriptions, usually
fits the experimental data over a wide range of concentrations. This isotherm gives an expression
encompassing the surface heterogeneity and the exponential distribution of active sites and their energies.
The Freundlich adsorption isotherms were also applied to the removal of Pb2+
on red mud (Fig.5. (b)).
efe CLnn
kLnqLn1
(3)
Where qe is the amount of metal ion sorbed at equilibrium per gram of adsorbent (mg/g), Ce the
equilibrium concentration of metal ion in the solution (mg/L), kf, and n the Freundlich model constants
[23, 24]. Freundlich parameters, kf and n, were determined by plotting ln qe versus ln Ce. The numerical
value of 1/n < 1 indicates that adsorption capacity is only slightly suppressed at lower equilibrium
concentrations. This isotherm does not predict any saturation of the sorbent by the sorbate; thus infinite
surface coverage is predicted mathematically, indicating multilayer adsorption on the surface [25].
The Langmuir and Freundlich adsorption constants from the isotherms and their correlation
coefficients are also presented in Table.2. The correlation factors R (0.999, and 0.802 for Langmuir, and
Freundlich model, respectively) confirm good agreement between both theoretical models and our
experimental results. The maximum sorption capacity, Q0, calculated from Langmuir equation is 18.87
mg/g, while Langmuir constant K is 0.35 L/mg. The values obtained for Pb2+
from the Freundlich model
showed a maximum adsorption capacity (Kf) of 9.93 mg/g with an affinity value (n) equal to 6.53.
The values indicate that the adsorption pattern for Pb2+
on red mud followed second the Langmuir
isotherm (R2 > 0.999), and the Freundlich isotherm (R
2 > 0.802) at all experiments.
Table 2: Langmuir and Freundlich isotherm parameters for the adsorption of lead on red mud.
Langmuir isotherm Freundlich isotherm
Q0(mg/g)
K(L/mg)
R2
18.87
0.35
0.999
Kf(mg/g)
n
R2
9.93
6.53
0.802
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Figure 5. (a) Langmuir and (b) Freundlich plots for lead adsorption on red mud (initial pH 7.5,
equilibrium contact time 2 h, adsorbent dosage 2 g/L, 300rpm agitating rate and temperature 20 ° C)
(a)
(b)
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It is clear that the Langmuir isotherm has best fitted for the sorption of Pb2+
on red mud. When
the system is in a state of equilibrium, the distribution of Pb2+
between the red mud and the Pb2+
solution
is of fundamental importance in determining the maximum sorption capacity of red mud for the Pb2+
ion
from the isotherm.
The values of the maximum adsorption capacities for the adsorption of Pb2+
cations on different
adsorbents used in the literature with adsorbent of the present study are summarized in Table 3. Although
direct comparison of the red mud with other adsorbent materials is difficult, owing to the differences in
experimental conditions, it was found that the maximum adsorption capacity of Jajarm red mud was 18.87
mg/g.
Table 3: Adsorption capacities of various adsorbents
Adsorbents Adsorption
capacity (mg/g)
Reference
Palm shell AC 95.20 [26]
Iron slag 17.20 [26]
RS1301 95.24 [26]
Rice husk 120.48 [27]
Peanut husk 29.14 [27]
Spent grain 35.5 [27]
Nipah palm shoot biomass 52.86 [27]
ZnO 6.70 [28]
Sawdust (pinus sylvestris) 9.78 [27]
Walnut sawdust 4.48 [27]
Bagasse fly ash 2.50 [27]
Jagarm red mud 18.87 Present work
3.2. Column adsorption experiments
3.2.1 Effect of flow rate
The adsorption columns were operated with different flow rates (5, 7 and 10 mL/min) until no
further lead removal was observed. The breakthrough curve for a column was determined by plotting the
ratio of the Ce/C0 (Ce and C0 are the lead concentrations of effluent and influent, respectively) against
time, as shown in Fig. 6. The column performed well at the lowest flow rate (5 mL/min). Earlier
breakthrough and exhaustion times were achieved, when the flow rate was increased from 5 to 10
mL/min. The column breakthrough time (Ce/C0=0.05) was reduced from 12 to 4 min, with an increase in
flow rate from 5 to 10 mL/min. This was due to a decrease in the residence time, which restricted the
contact of lead solution to the red mud. At higher flow rates the lead ions did not have enough time to
diffuse into the pores of the red mud and they exited the column before equilibrium occurred. Similar
results have been found for As (III) removal in a fixed-bed system using modified calcined bauxite and
for color removal in a fixed-bed column system using surfactant-modified zeolite [29, 30].
3.2.2 Effect of initial Lead concentration
The adsorption breakthrough curves obtained by changing initial lead concentration from 30 to 50
mg Pb/L at 5 mL/min flow rate and 50 mm bed depth are given in Fig. 7. As expected, a decrease in lead
concentration gave a later breakthrough curve; the treated volume was greatest at the lowest transport due
to a decreased diffusion coefficient or mass transfer coefficient [31]. Breakthrough time (Ce/C0=0.05)
occurred after 16.5 min at 30 mg/L initial lead concentration while the breakthrough time was 8 min at 50
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mg/L. The breakthrough time decreased with increasing lead concentration as the binding sites became
more quickly saturated in the column.
Figure 6. Breakthrough curves expressed as Ce/C0 versus time at different flow rates (initial lead
concentration 40 mg/L, initial pH 7.5, bed depth 50 mm and temperature 20 ±1°C)
Successful design of a column lead adsorption process requires a description of the dynamic
behavior of lead ion in a fixed bed. Various simple mathematical models have been developed to describe
and possibly predict the dynamic behavior of the bed in column performance [32]. One model used for
continuous flow conditions is the Thomas model [33], which can be written as:
(4)
where, kth is the Thomas model constant (L/mg h), q0 is the adsorption capacity (mg/g), Q is the
volumetric flow rate through column (L/h),m is the mass of adsorbent in the column (g), C0 is the initial
lead concentration (mg/L) and Ce is the effluent lead concentration (mg/L) at any time t (h). The Thomas
model constants kth and q0 were determined from a plot of ln [C0/Ce−1] versus t at a given flow rate. The
model parameters are given in Table 4. The Thomas model gave a good fit of the experimental data, at all
the flow rates examined, with correlation coefficients greater than 0.970, which would indicate that the
external and internal diffusions were not the rate limiting step [32]. The rate constant (kth) decreased with
increasing initial Lead concentration which indicates that the mass transport resistance increases. The
reason is that the driving force for adsorption is the lead concentration difference between red mud and
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solution [32, 34].
Figure 7. Breakthrough curves expressed as Ce/C0 versus time at different lead concentrations (initial pH
7.5, flow rate 5 mL/min, bed depth 50 mm and temperature 20 ±1°C)
Table 4. The Thomas model and BDST model parameters for the adsorption of lead on red mud
The Thomas model parameters
Lead concentration (mg/L) q0 (mg/g) kth (L/mg h) R2
30
40
50
54.06
59.14
59.30
0.0037
0.0027
0.0025
0.996
0.970
0.976
The BDST model parameters
N (mg/L) Kα (L/mg h) R2
360.26 0.5936 0.868
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3.2.3 Effect of bed height
The accumulation of lead in a fixed-bed column is dependent on the quantity of adsorbent inside
the column. In order to study the effect of bed height on lead retention, red mud of three different bed
heights, viz. 50, 70, and 100 mm, were used. A lead solution of fixed concentration (40 mg Pb/L) was
passed through the fixed-bed column at a constant flow rate of 5 mL/min. As depicted by Fig. 8 the
breakthrough time varied with bed height. Steeper breakthrough curves were achieved with a decrease in
bed depth. The breakthrough time decreased with a decreasing bed depth from 100 to 50 mm, as binding
sites were restricted at low bed depths. At low bed depth, the lead ions do not have enough time to diffuse
into the surface of the red mud, and a reduction in breakthrough time occurs. Conversely, with an increase
in bed depth, the residence time of lead solution inside the column was increased, allowing the lead ions
to diffuse deeper into the red mud.
Figure 8. Breakthrough curves expressed as Ce/C0 versus time at different bed depth (initial lead
concentration 40 mg/L, initial pH 7.5, flow rate 5 mL/min and temperature 20 ±1°C)
The breakthrough service time (BDST) model is based on physically measuring the capacity of
the bed at various percentage breakthrough values. The BDST model constants can be helpful to scale up
the process for other flow rates and concentrations without further experimentation. It is used to predict
the column performance for any bed length, if data for some depths are known. It states that the bed
depth, Z and service time, t of a column bears a linear relationship. The rate of adsorption is controlled by
the surface reaction between adsorbate and the unused capacity of the adsorbent.
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Figure 9. Plot of BDST equation for lead adsorption on red mud
The BDST equation can be expressed as follows [35]:
(5)
where Cb is the breakthrough lead concentration (mg/L), N is the adsorption capacity of bed (mg/L), Z is
depth of column bed (cm), v is the linear flow velocity of lead solution through the bed (mL/cm2 h), Kα is
the rate constant (L/mg h). The column service time was selected as the time when the normalized
concentration, Ce/C0 reached 0.05. A plot of service time versus bed depth, at a flow rate of 5 mL/min
(Fig. 9) was linear. The correlation coefficient value (R2=0.868) indicated the validity of the BDST model
for the present system. The values of BDST model parameters are presented in Table 4. The value of Kα
characterizes the rate of transfer from the fluid phase to the solid phase. If Kα is large, even a short bed
will avoid breakthrough, but as Kα decreases a progressively deeper bed is required to avoid
breakthrough.
4. CONCLUSIONS
In this study, the lead adsorption capacity of red mud was evaluated for batch and fixed-bed
column adsorption systems. Batch experiments indicated that the time to attain equilibrium was 2 h. The
adsorption of lead on red mud in batch systems can be described by the Langmuir isotherm, and the
adsorption capacity was 18.87 mg/g. The fixed-bed column breakthrough curves were analyzed at
different flow rates, bed depth and initial lead concentration. Thomas and BDST models were
successfully used for predicting breakthrough curves for lead removal by a fixed bed of red mud using
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different initial lead concentration and bed depths. Despite its slightly low performance, the use of red
mud as an adsorbent for lead removal is potentially cost-effective and may provide an alternative method
for lead removal from contaminated water.
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